Web Mining for Personalization: A Survey in the Fuzzy Framework
Keywords:web mining, personalization, fuzzy, clustering
Web mining is the use of data mining techniques to automatically discover and extract information from Web documents and services. When comparing web mining with traditional data mining, there are three main differences to consider: Scale, AccessÂ and Structure. Web personalization is the process of tailoring content that web user experiences according to his needs, goals and preferences. In this survey paper we have discussed various researches done in the field of web mining for personalization in last fifteen which used fuzzy as their framework for study. We also discussed a fuzzy c-means clustering algorithm which we will consider in our further research.
Dragos Arotariteia, Sushmita Mitrab, â€œWeb mining: a survey in the fuzzy frameworkâ€. Elsevier- Fuzzy Sets and Systems, 2004.
Fernando Crespoa, Richard Weberb, â€œA methodology for dynamic data mining based on fuzzy clusteringâ€. Elsevier- Fuzzy Sets and Systems, March ,2004.
Raghu Krishnapuram, , Anupam Joshi, Olfa Nasraoui, â€œLow-Complexity Fuzzy Relational Clustering Algorithms for Web Miningâ€. IEEE Transactions on fuzzy systems, Vol 9, No. 4, August 2001.
Chunlai Chai, Biwei Li, â€œA Novel Association Rules Method Based on Genetic Algorithm and Fuzzy Set Strategy for Web Miningâ€. Journal of computers, Vol. 5, No. 9, September 2010.
. Sendhilkumar, K. Selvakumar and G.S. Mahalakshmi, â€œApplications of fuzzy logic for user classification in personalized webâ€. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014.
Suruchi Chawla,â€ Clusterwise optimization of clicked web pages using Genetic algorithm for effective Personalized Web Searchâ€ International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 4, Issue 1, January â€“ February 2015.
Setu Kumar Chaturvedi , Deepak Kumar Niware ,â€ Web Usage Mining through Efficient Genetic Fuzzy C-Meansâ€. IJCSNS International Journal of Computer Science and Network Security, VOL.14 No.6, June 2014.
Anupam Joshi, Raghu Krishnapuram, â€œRobust Fuzzy Clustering Methods to Support Web Miningâ€. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.41.4287&rep=rep1&type=pdf
Kyung-Joong Kim , Sung-Bae Cho, â€œPersonalized mining of web documents using link structures and fuzzy concept networksâ€. Elsevier- Fuzzy Sets and Systems ,September 2005.
Neelam Sain, Prof. Sitendra Tamrakar, â€œA Survey of Web Usage Mining based on Fuzzy Clustering and HMMâ€. (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 3 (4) , 2012.
Dibya Jyoti Bora, Dr. Anil Kumar Gupta, â€œA Comparative study Between Fuzzy Clustering Algorithm and Hard Clustering Algorithmâ€. International Journal of Computer Trends and Technology (IJCTT) â€“ volume 10 number 2 â€“ Apr 2014.
M.S.. Yang, â€œA Survey of Fuzzy Clusteringâ€. Mathl. Comput. Modelling Vol. 18, No. 11, pp. 1-16, 1993, Great Britain.
K. M. Bataineh,a, M. Najia, M. Saqera , â€œA Comparison Study between Various Fuzzy Clustering Algorithmsâ€. 343 Jordan Journal of Mechanical and Industrial Engineering, Volume 5, Number 4, Aug. 2011.
Md. Ehsanul Karim, Feng Yun, Sri Phani Venkata Siva Krishna Madani, â€œFuzzy Clustering Analysisâ€. Thesis in Mathematical Modelling and Simulation , Blekinge institute of technology,2010-august.
Leehter Yao and Kuei-Sung Weng, â€œOn A Type-2 Fuzzy Clustering Algorithmâ€. PATTERNS 2012: The Fourth International Conferences on Pervasive Patterns and Applications.
, James C Bedzec, Roberst Ehrlich, William Full, â€FCM : The fuzzy c- means clustering algorithmâ€. Computers and geosciences, vol. 10 , no. 2-3, 1984, USA.
Pooja Mehtaa, Brinda Parekh, Kirit Modi, and Paresh Solanki,â€ Web Personalization Using Web Mining: Concept and Research Issueâ€. International Journal of Information and Education Technology, Vol. 2, No. 5, October 2012.
Mr. Ankit R. Deshmukh, Prof. Sunil R. Gupta,â€ DATA MINING BASED SOFT COMPUTING METHODS FOR WEB INTELLIGENCEâ€, International Journal of Application or Innovation in Engineering & Management (IJAIEM), Volume 3, Issue 3, March 2014.
M. Gomathi ,â€ A Survey on Web Mining Using Fuzzy Logicâ€, International Journal of Advanced Research in Computer Science and Software Engineering,Volume 5, Issue 3, March 2015.
Fernando Crespoa, Richard Weberb,â€ A methodology for dynamic data mining based on fuzzy clusteringâ€, Elsevier- science direct, Fuzzy Sets and Systems 150 (2005) 267â€“284.
MarÃa J. MartÃn-Bautista, MarÃa-Amparo Vila, â€œObtaining user profiles via web usage miningâ€, IADIS European Conference Data Mining, Granada (Spain),2008.
Bo Pang and Lillian Lee, â€œOpinion Mining and Sentiment Analysis â€œ. Foundations and Trends in Information Retrieval ,Vol. 2, Nos. 1â€“2 ,2008 .
Limin Ren, â€œ Research of Web Data Mining Based on Fuzzy Logic and Neural Networksâ€. IEEE: Fuzzy Systems and Knowledge Discovery FSKDâ€™09,Vol. 3, 2009.
Binu Thomas and G. Raju, â€œA Novel Web Classification Algorithm Using Fuzzy Weighted Association Rulesâ€. Article in ISRN Artificial Intelligence Volume 2013, Hindawi Publishing Corporation â€“ 2013.
Pawan Lingras, Chad West, â€œInterval Set Clustering of Web Users with Rough K â€“Meansâ€. Journal of Intelligent Information Systems, Springer ,Volume 23, Issue 1, July 2004.
Francisco Herrera, â€œGenetic fuzzy systems: taxonomy, current research trends and prospectsâ€. Evolutionary Intelligence â€“ Springer, Volume 1, Issue 1, pp 27-46, March 2008.
Qingyu Zhang and Richard S. Segall, â€œWeb mining â€œ a survey of current research , techniques, and softwareâ€. Article in KYBERNETES , MAY 2010.
How to Cite
- Papers must be submitted on the understanding that they have not been published elsewhere (except in the form of an abstract or as part of a published lecture, review, or thesis) and are not currently under consideration by another journal published by any other publisher.
- It is also the authors responsibility to ensure that the articles emanating from a particular source are submitted with the necessary approval.
- The authors warrant that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required.
- The authors ensure that all the references carefully and they are accurate in the text as well as in the list of references (and vice versa).
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-NonCommercial 4.0 International that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.